Predictors of physical functioning after total hip arthroplasty: a systematic review
Bibliographic record
Abstract
OBJECTIVE: The objective of this systematic review of the literature was to identify the predictors of functional outcome after total hip arthroplasty (THA). METHOD: A systematic literature search in Web of Science, CINAHL, EMBASE and PubMed was conducted on 23 June 2015. The articles were selected based on their quality, relevance and measurement of the predictive factor. The level of evidence of all studies was determined using the GRADE rating scheme. RESULTS: The initial search resulted in 1092 citations. After application of the inclusion and exclusion criteria, 33 articles met our eligibility criteria and were graded. Included studies were classified as level of evidence low (11), moderate (17) or high (5). Of the included studies, 18 evaluated body mass index (BMI), 17 evaluated preoperative physical functions, 15 evaluated age, 15 evaluated gender and 13 evaluated comorbidity. There was strong evidence suggesting an association between BMI, age, comorbidity, preoperative physical functions and mental health with functional outcome after THA. There was weak evidence suggesting an association between quadriceps strength and education with functional outcome after THA. The evidence was inconsistent for associations with gender and socioeconomic status and functional outcome following THA. We found limited evidence suggesting that alcohol consumption, vitamin D insufficiency and allergies were predictors of functional outcome following THA. CONCLUSIONS: We have identified multiple predictors of functional outcome after THA, which will enable general practitioners and orthopaedic surgeons to better predict the improvement in physical functioning for their patients with THA. They can use this information to provide patient-specific advice regarding the referral for THA and the expected outcomes after THA. Further research with consistent measurement tools, outcomes and duration of follow-up across studies is needed to confirm the influence of these factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".